Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods or our paper for further explanation).

Using data available up to the: 2020-06-18

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-06-07) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-06-07 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmedcases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-07 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-07 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-07 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-07 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-06-07)

Table 1: Latest estimates (as of the 2020-06-07) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Country New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling/halving time (days)
Afghanistan 716 (637 – 775) Likely increasing 1 (1 – 1.1) 140 (32 – -60)
Albania 54 (38 – 66) Increasing 1.4 (1.1 – 1.6) 8 (4.7 – 27)
Algeria 118 (95 – 136) Unsure 1 (0.9 – 1.2) 63 (15 – -28)
Andorra 6 (0 – 14) Unsure 1.1 (0 – 2.3) -14 (1.7 – -1.3)
Argentina 1380 (1267 – 1499) Increasing 1.2 (1.1 – 1.2) 16 (12 – 22)
Armenia 558 (493 – 610) Increasing 1.1 (1 – 1.1) 71 (25 – -82)
Australia 14 (6 – 21) Unsure 1.3 (0.8 – 1.8) 9.8 (3.5 – -11)
Austria 29 (19 – 38) Unsure 1 (0.7 – 1.2) -96 (11 – -9)
Azerbaijan 370 (327 – 409) Increasing 1.1 (1 – 1.2) 31 (16 – 620)
Bahrain 542 (497 – 600) Likely increasing 1 (1 – 1.1) 71 (26 – -98)
Bangladesh 3406 (3137 – 3651) Increasing 1.1 (1.1 – 1.2) 25 (20 – 35)
Belarus 777 (711 – 844) Unsure 1 (0.9 – 1) -140 (76 – -37)
Belgium 108 (88 – 126) Unsure 0.9 (0.8 – 1.1) -77 (26 – -16)
Benin 35 (24 – 47) Increasing 1.5 (1.1 – 1.9) 6.1 (3.6 – 20)
Bolivia 765 (691 – 835) Increasing 1.2 (1.1 – 1.3) 16 (12 – 26)
Bosnia and Herzegovina 44 (31 – 54) Likely increasing 1.2 (0.9 – 1.4) 15 (6.5 – -44)
Brazil 27122 (25672 – 28606) Increasing 1 (1 – 1.1) 84 (54 – 190)
Bulgaria 81 (66 – 97) Likely increasing 1.2 (1 – 1.4) 16 (7.7 – -210)
Cameroon 267 (236 – 293) Unsure 1 (0.9 – 1.1) -200 (35 – -26)
Canada 432 (388 – 470) Decreasing 0.9 (0.8 – 0.9) -20 (-40 – -13)
Central African Republic 79 (63 – 94) Unsure 0.9 (0.8 – 1.1) -26 (48 – -10)
Chad 5 (0 – 9) Unsure 0.9 (0.2 – 1.7) -15 (3 – -2.2)
Chile 6134 (5688 – 6562) Increasing 1.1 (1.1 – 1.1) 25 (20 – 31)
China 33 (19 – 42) Increasing 1.6 (1.2 – 2.1) 4.7 (2.9 – 12)
Colombia 1930 (1720 – 2102) Increasing 1.2 (1.1 – 1.2) 19 (14 – 29)
Congo 27 (17 – 36) Likely increasing 1.3 (1 – 1.6) 9.5 (4.5 – -69)
Costa Rica 55 (40 – 70) Likely increasing 1.1 (0.9 – 1.3) 27 (8.4 – -24)
Cote dIvoire 235 (204 – 260) Increasing 1.2 (1.1 – 1.3) 16 (9.8 – 40)
Croatia 5 (0 – 9) Likely increasing 2.2 (0.5 – 3.8) 2.9 (1.2 – -5.9)
Cuba 13 (5 – 19) Unsure 0.9 (0.6 – 1.3) -23 (8.2 – -4.7)
Czechia 55 (40 – 68) Unsure 1 (0.8 – 1.2) 110 (12 – -15)
Democratic Republic of the Congo 102 (85 – 121) Likely decreasing 0.9 (0.8 – 1) -26 (65 – -11)
Denmark 39 (27 – 50) Unsure 1 (0.8 – 1.3) 91 (9.5 – -12)
Djibouti 33 (21 – 43) Decreasing 0.6 (0.4 – 0.8) -6.6 (-18 – -4)
Dominican Republic 481 (430 – 525) Increasing 1.1 (1 – 1.2) 24 (14 – 69)
Ecuador 602 (537 – 667) Increasing 1.1 (1 – 1.2) 34 (19 – 200)
Egypt 1651 (1495 – 1777) Increasing 1.1 (1.1 – 1.2) 25 (19 – 40)
El Salvador 106 (85 – 122) Likely increasing 1.1 (1 – 1.2) 25 (10 – -68)
Equatorial Guinea 47 (34 – 61) Unsure 1.1 (0.8 – 1.3) -110 (11 – -9.4)
Estonia 11 (1 – 19) Unsure 1 (0.4 – 1.6) -37 (4.6 – -3.8)
Ethiopia 184 (156 – 206) Likely increasing 1.1 (1 – 1.2) 27 (12 – -180)
Finland 18 (9 – 27) Unsure 1 (0.6 – 1.3) -87 (7.7 – -6.6)
France 454 (409 – 495) Unsure 1 (0.9 – 1.1) -74 (52 – -22)
Gabon 124 (98 – 148) Increasing 1.3 (1.1 – 1.5) 11 (6.4 – 31)
Germany 340 (302 – 376) Unsure 1 (0.9 – 1.1) -2000 (33 – -33)
Ghana 310 (275 – 351) Increasing 1.1 (1 – 1.2) 29 (15 – 410)
Greece 17 (9 – 25) Unsure 1 (0.7 – 1.4) -460 (7.4 – -7.3)
Guatemala 429 (381 – 476) Increasing 1.1 (1.1 – 1.2) 20 (13 – 44)
Guinea 56 (42 – 68) Unsure 1 (0.8 – 1.2) 1800 (13 – -13)
Guinea Bissau 17 (9 – 24) Unsure 1.2 (0.8 – 1.7) 8.3 (3.6 – -26)
Haiti 131 (108 – 149) Likely decreasing 0.9 (0.8 – 1) -23 (190 – -11)
Honduras 383 (346 – 413) Increasing 1.2 (1.1 – 1.3) 13 (8.5 – 24)
Hungary 16 (6 – 24) Unsure 1.1 (0.6 – 1.5) 43 (5.3 – -6.8)
Iceland 4 (0 – 9) Likely increasing 2.3 (0.4 – 4.2) 2.2 (1 – -4.1)
India 11616 (10855 – 12456) Increasing 1.1 (1.1 – 1.1) 30 (25 – 38)
Indonesia 1084 (1003 – 1182) Increasing 1.2 (1.1 – 1.2) 18 (14 – 28)
Iran 2480 (2267 – 2667) Unsure 1 (1 – 1.1) -270 (59 – -40)
Iraq 1243 (1139 – 1357) Increasing 1.2 (1.1 – 1.2) 22 (16 – 36)
Ireland 18 (9 – 25) Unsure 0.9 (0.6 – 1.2) -36 (8.8 – -5.9)
Israel 205 (173 – 234) Increasing 1.2 (1.1 – 1.4) 14 (8.7 – 32)
Italy 295 (258 – 333) Unsure 1 (0.9 – 1.1) 120 (24 – -39)
Japan 57 (40 – 70) Likely increasing 1.2 (0.9 – 1.4) 16 (6.9 – -44)
Kazakhstan 328 (285 – 370) Increasing 1.2 (1 – 1.3) 15 (9.9 – 33)
Kenya 127 (107 – 147) Unsure 1 (0.9 – 1.2) 180 (18 – -24)
Kosovo 40 (28 – 50) Likely increasing 1.3 (1 – 1.6) 11 (5.4 – -120)
Kuwait 581 (530 – 630) Likely decreasing 1 (0.9 – 1) -87 (84 – -29)
Kyrgyzstan 69 (50 – 83) Increasing 1.3 (1.1 – 1.5) 9.4 (5.5 – 33)
Latvia 7 (0 – 16) Unsure 1.6 (0.3 – 2.7) 5.9 (1.8 – -4.6)
Lebanon 18 (9 – 26) Unsure 1 (0.7 – 1.4) 100 (6.6 – -7.9)
Libya 25 (14 – 33) Unsure 1.1 (0.8 – 1.4) 26 (6.6 – -13)
Lithuania 11 (4 – 18) Unsure 1.2 (0.7 – 1.8) 17 (3.9 – -6.9)
Luxembourg 8 (1 – 13) Likely increasing 1.4 (0.7 – 2.2) 8.1 (2.6 – -7.5)
Madagascar 29 (18 – 38) Unsure 0.9 (0.7 – 1.1) -23 (19 – -7)
Malawi 21 (10 – 30) Unsure 1.1 (0.7 – 1.5) 17 (4.9 – -11)
Malaysia 28 (16 – 38) Likely decreasing 0.8 (0.5 – 1) -6.8 (-42 – -3.7)
Maldives 24 (13 – 32) Unsure 1.1 (0.7 – 1.4) 15 (5.1 – -17)
Mali 42 (31 – 55) Unsure 1.1 (0.8 – 1.3) 56 (9.6 – -14)
Mauritania 141 (116 – 160) Increasing 1.3 (1.1 – 1.5) 9.6 (6.3 – 20)
Mexico 4494 (4219 – 4783) Increasing 1.1 (1.1 – 1.1) 35 (26 – 54)
Moldova 318 (282 – 359) Increasing 1.2 (1.1 – 1.3) 16 (11 – 34)
Mongolia 5 (0 – 9) Unsure 1.2 (0.2 – 2.2) 15 (1.9 – -2.7)
Morocco 77 (62 – 93) Unsure 1 (0.9 – 1.2) 98 (14 – -19)
Nepal 364 (329 – 394) Increasing 1.1 (1 – 1.2) 27 (15 – 150)
Netherlands 178 (148 – 202) Unsure 1 (0.9 – 1.1) 110 (19 – -29)
New Zealand 4 (0 – 10) Likely increasing 2.9 (0.2 – 5.7) 0.43 (0.45 – -0.84)
Niger 7 (2 – 12) Likely increasing 1.7 (0.8 – 2.5) 4.9 (2.1 – -14)
Nigeria 555 (500 – 608) Increasing 1.2 (1.1 – 1.3) 15 (11 – 25)
North Macedonia 146 (125 – 167) Likely increasing 1.1 (1 – 1.2) 46 (15 – -38)
Norway 14 (7 – 21) Unsure 1 (0.6 – 1.3) -45 (8.1 – -6)
Oman 1045 (947 – 1141) Increasing 1.1 (1.1 – 1.2) 20 (14 – 32)
Pakistan 6078 (5704 – 6465) Increasing 1.1 (1.1 – 1.2) 23 (19 – 29)
Palestine 7 (2 – 12) Unsure 1.3 (0.6 – 2) 9.7 (2.8 – -6.5)
Panama 683 (614 – 749) Increasing 1.2 (1.1 – 1.3) 15 (11 – 24)
Paraguay 21 (11 – 29) Unsure 1 (0.7 – 1.3) -150 (8.5 – -7.6)
Peru 4882 (4606 – 5159) Increasing 1 (1 – 1.1) 60 (37 – 170)
Philippines 566 (517 – 616) Unsure 1 (1 – 1.1) 110 (31 – -71)
Poland 418 (369 – 460) Unsure 1 (0.9 – 1.1) 500 (32 – -37)
Portugal 316 (278 – 351) Unsure 1 (0.9 – 1.1) 190 (27 – -37)
Puerto Rico 112 (90 – 131) Likely decreasing 0.9 (0.8 – 1) -15 (-73 – -8.1)
Qatar 1543 (1449 – 1647) Unsure 1 (0.9 – 1) -190 (110 – -50)
Romania 243 (210 – 277) Increasing 1.2 (1 – 1.3) 19 (11 – 65)
Russia 9099 (8499 – 9619) Increasing 1 (1 – 1.1) 79 (49 – 190)
Saudi Arabia 4124 (3803 – 4451) Increasing 1.2 (1.1 – 1.2) 15 (13 – 18)
Senegal 103 (82 – 121) Unsure 1 (0.9 – 1.2) 270 (17 – -19)
Serbia 71 (55 – 85) Unsure 1.1 (0.9 – 1.2) 77 (13 – -19)
Sierra Leone 29 (18 – 38) Likely increasing 1.1 (0.9 – 1.4) 19 (6.3 – -18)
Singapore 358 (316 – 390) Unsure 1 (0.9 – 1) -86 (55 – -24)
Slovakia 6 (1 – 10) Likely increasing 1.7 (0.7 – 2.7) 4.8 (1.8 – -8.1)
Somalia 39 (25 – 51) Unsure 0.9 (0.7 – 1.1) -32 (17 – -8.2)
South Africa 3449 (3146 – 3722) Increasing 1.2 (1.1 – 1.2) 17 (14 – 21)
South Korea 45 (31 – 55) Unsure 1 (0.8 – 1.2) 150 (11 – -13)
South Sudan 34 (23 – 45) Decreasing 0.8 (0.6 – 1) -8.6 (-30 – -5)
Spain 341 (305 – 379) Unsure 1 (0.9 – 1.1) 38 (17 – -210)
Sri Lanka 10 (5 – 17) Likely decreasing 0.7 (0.4 – 1) -7.3 (23 – -3.2)
Sudan 203 (178 – 230) Increasing 1.1 (1 – 1.2) 23 (12 – 350)
Sweden 1067 (986 – 1151) Increasing 1.1 (1 – 1.1) 67 (27 – -150)
Switzerland 23 (15 – 32) Likely increasing 1.2 (0.9 – 1.5) 17 (5.6 – -16)
Tajikistan 70 (54 – 85) Likely decreasing 0.9 (0.7 – 1) -22 (57 – -8.9)
Thailand 6 (1 – 10) Unsure 1.1 (0.4 – 1.7) 75 (3.5 – -4)
Tunisia 8 (1 – 12) Likely increasing 1.9 (0.8 – 2.9) 3.2 (1.6 – -200)
Turkey 1374 (1232 – 1520) Increasing 1.2 (1.1 – 1.2) 15 (12 – 20)
Uganda 12 (5 – 18) Likely decreasing 0.8 (0.5 – 1.1) -9.5 (23 – -4)
Ukraine 676 (606 – 743) Increasing 1.2 (1.1 – 1.3) 15 (10 – 24)
United Arab Emirates 468 (424 – 505) Decreasing 0.9 (0.9 – 1) -33 (-180 – -18)
United Kingdom 1400 (1300 – 1507) Likely decreasing 1 (0.9 – 1) -100 (110 – -35)
United Republic of Tanzania 10 (3 – 15) Decreasing 0.7 (0.4 – 1) -8.4 (33 – -3.7)
United States of America 23452 (21876 – 24970) Increasing 1.1 (1 – 1.1) 49 (36 – 76)
Uzbekistan 145 (120 – 164) Likely increasing 1.1 (1 – 1.3) 24 (11 – -160)
Venezuela 77 (60 – 93) Likely decreasing 0.9 (0.7 – 1) -18 (1800 – -8.7)
Yemen 55 (41 – 71) Increasing 1.4 (1.1 – 1.7) 7.7 (4.5 – 26)
Zambia 30 (19 – 40) Likely increasing 1.2 (0.9 – 1.5) 17 (5.8 – -20)
Zimbabwe 16 (8 – 24) Unsure 1.1 (0.7 – 1.5) 41 (5.5 – -7.8)